Cameras are commonly used to capture an image of a scene. Unfortunately, some of the captured images are blurred. FIG. 1 is a simplified illustration of a prior art, blurred, captured image 14P of a starfish. In this illustration, the relatively thick lines are used to represent the blurring of the captured image 14P.
A number of different methods exist for deblurring an image. For example, blurring of an image is commonly modeled as convolution and many deconvolution methods exist that can help to reduce blurring. However, most of these methods tend to produce ringing artifacts in the reconstructed image.
One commonly used deconvolution method is the Lucy-Richardson deconvolution method. FIG. 1 also illustrates a prior art reconstructed image 26P that was deconvouted using the Lucy-Richardson method. Although this method works quite well in reducing blurring, the reconstructed image is left with two types of ringing artifacts, namely ringing artifacts around the edges and other boundaries of objects in the image, and ringing artifacts around boundaries of the image (e.g. the image border). As a result thereof, the resulting reconstructed image 26P has ringing artifacts 28P (illustrated with two dashed lines) around the edges 30P of the captured object(s) 20P in the reconstructed image 26P, and has ringing artifacts 32P (illustrated with two dashed lines) around the boundaries 34P of the reconstructed image 26P. The ringing in the reconstructed image 26P typically consists of multiple parallel lines around the object 20P and image edges 34P, with the first line being the strongest and subsequent lines gradually become weaker.
As the result thereof, the corrected image is not completely satisfactory.